Highly Stretchable Strain Sensor based on 3D Nanostructure for Human Motion Detection System

October 14, 2017

The demand for wearable strain gauges that can detect dynamic human motions is growing in the area of healthcare technology. However, the realization of efficient sensing materials for the effective detection of human motions in daily life is technically challenging due to the absence of optimally designed electrodes. Here, we propose a novel concept to overcome the intrinsic limits of conventional strain sensors based on planar electrodes by developing highly periodic and three-dimensional (3D) bicontinuous nanoporous electrodes. The 3D structural platform allows the fabrication of a strain sensor with robust properties, such as a gauge factor of up to 134 at a tensile strain of 40%, a widened detection range of up to 160%, and a cyclic property of over 1000 cycles. Collectively, this study provides new design opportunities for a highly efficient sensing system that finely captures human motions, including phonations and joint movements.

As a research project of the Global Frontier Program – KAIST Advanced Battery Center, Professor Seokwoo Jeon’s research team is working on the development of a stretchable electrode system with various three-dimensional (3D) nanostructures using a scalable lithographic technique. The project was started in 2016 to develop and optimize a stretchable and conductive 3D nanostructure as a wearable strain gauge for detecting human motions. The real-time and sensitive detection of human motion (i.e., phonation and joint movement) is of great importance for ubiquitous healthcare technology. In the past decade, there have been numerous efforts to develop body-attachable human−machine interfaces based on flexible and stretchable conductors. Among these developments, a resistance-mode wearable strain gauge has been showing great potential for commercialization due to its reliability and simplicity. To achieve a high-quality resistance-mode strain gauge, three major aspects of technical development should be satisfied: (1) improving sensitivity (i.e., a gauge factor over 200%), (2) widening the working strain range, and (3) retaining the intrinsic piezoresistive properties without severe performance degradation after repeated usage.

Herein, we demonstrate a highly sensitive and stretchable strain gauge consisting of a 3D continuous percolation network of single-walled carbon nanotubes (SWCNTs) formed along a 3D nanostructured porous elastomer polydimethylsiloxane (PDMS). The uniformly interconnected 3D nanostructure can greatly improve the stretchability (>200%) of the sensor. In addition, the structure enables efficient electrical percolation of conductive networks even at an extremely low concentration of SWCNTs (0.9 vol%), leading to dramatically increased sensitivity.

Figure 1. Concept and strategy for achieving a 3D bicontinuous nanoporous electrode. (a) Schematic illustration of the fabrication procedure for the 3D continuous conductive nanostructure and its demonstration as a 3D electrode for a strain sensor. (b) Photographs of the highly stretchable 3D PDMS before and after stretching of ε = 220%. (c) Top view SEM image of a 20% stretched 3D continuous conductive nanostructure after removal of a part of the first layer (scale bar, 1 μm). (d) Photographs of 3D strain sensors attached to the finger, neck, and wrist to detect dynamic human motions, such as phonations and joint movements.
The main contribution of this work is the first development of the solid-state, conductive 3D nanonetwork with optimal percolations that can maximize the performance of resistive strain sensors, as demonstrated by the highest gauge factor of ∼134 among CNT-based sensors reported to date. To achieve this, we have solved the dispersion problem of CNTs in the 3D nanostructured elastomeric matrix by surface treatment even at an extremely low concentration of CNTs (<1 vol %). Therefore, the solid-state, conductive 3D nanonetwork suggests a possible strategy for applications that require high sensitivity, such as capturing delicate phonations and dynamic detection of human joint motions.